What it is about
You will learn how to analyze large datasets — in particular text and network data — with Python. By the end you can collect, clean, transform and analyze data with standard libraries; moreover you will apply basic statistics, visualization and machine learning methods to your own research questions.
What you will be able to do
- Data collection and reading (including web scraping and APIs)
- Selecting, cleaning, merging and reshaping data
- Text analysis: preprocessing, POS, NER, vectorization, topic modeling
- Network analysis: metrics, centrality, diffusion simulations
- Application of statistical methods (correlation, t-test, chi-squared)
- Application of basic ML methods: regression, classification, clustering
What the module consists of
- VorlesungPresentation of new topics and concepts
- Übung / In‑class exercisesPractical implementation and application of the concepts in Python
Teaching method
- VorlesungIntroduction to new topics
- In‑class ÜbungenImplementation and application of the presented methods in Python